Challenge Data Visualization Five Essential Principles

No matter what shape you are putting in terms of health and well-being, shopping habits, or editorials, the Orfitur Group summarizes the following five core principles of data visualization that challenge the following.

In the early days of the digital era, data was tinker with mathematicians and scientists. Today, no matter in any field, anyone can not escape the discussion and study of the data. Not only are online services dependent on data, we are also sources of data that generates an endless stream of information about all aspects of our lives.

Whether it's human data-thanks to the rise of wearable devices-our energy consumption at home, or our personal financial-related data: the data we generate is generated by large amounts of data, and for now we need to find ways to understand what it means to us.

Personalized data raises a wave of heat among businesses to gather customer information and seek value from customers. The challenge for designers is how to find ways to reduce the complexity of large amounts of data and give the data a prototype that is easy to humanize.

Data are available to everyone. It provides users with meaningful and easy to understand practical ways. Here's where the power of design differs: It helps improve people's lives by helping people find their way through the vast data world.

Data visualization has come a long way since the invention of the basic pie chart more than 200 years ago. Nowadays, due to the advent of data tide and people's discussion of data usage, a new design language is emerging which can beautifully simplify the complexity of big data into a visual image that is beautiful and meaningful.

So no matter what shape you are putting in terms of health and well-being, shopping habits or in editorials, the Orfitull team concludes with the following five core principles to face when facing data visualization challenges.

Understand the data source

Make sure you understand the data for your job. This is a crucial first step in understanding the data. You need to understand the macro world: Why do you collect the data? What values ​​do companies give to the data? Who are the users? How can the data be maximized? Understanding these issues in depth helps to create both meaningful Humanized visual information, lay an important foundation.

2 clear the story you want to talk about

Good data visualization is more than just a beautiful picture, it tells a story anyone can understand. Therefore, it is crucial that you first identify the story you want to tell and then use the data as a way of polishing the story.

For example, we recently helped the Swedish mobile operator "3" to redesign the monthly mobile phone bill that was previously confusing to users, making it user-centric and user-friendly. 3 The company hopes to design more efficient and easy to use bills, rather than continue to show the user a string of numbers difficult to understand.

Good data visualization tells a story that everyone can understand.

The result of our work is a "my 3" APP app that allows users to see the package status in real time to see what the package is. Through data visualization, we designed a beautiful and innovative way for users to view the data. It also shows the company's customer relationship.

3. Define the user experience

Make sure you use the data for guidance and not for the entire experience. Data users should play a role in the process of understanding and learning and developing their own experiences. What is worth exploring is how to integrate your insights into your visualization data so that users can interpret the data flexibly that makes sense to the user. After all, delightful experiences make it easy for users to remember and reuse.

4 simple rules

Data visualization is used to inform users rather than let users receive unwanted overload information. The role of a designer, your role is to focus on simple, complex or fragmented information becomes feasible, easy to understand, meaningful and more humane information. Remember, the easier it is for users to understand.

5. Avoid repeating the invention of wheels

Try typing the current behavior into your visualization. Will make your design is widely accepted by the user community. The reason why pie charts are widely used is that people understand what it means. This is a natural and elegant visual design, because it has greater influence, and can make people see it.

A design-driven approach

Good data visualization is not only a masterpiece of design, but also a valuable tool for helping people to interpret previously inaccessible content and make them meaningful and instructive. As more and more companies begin to realize the potential energy of data, design will play a bigger role in turning things that are less clear into things that help people. The key is to use the user first, focus on simple design-driven approach to create a never-ending pleasure experience.